An intelligent monitoring system for fishery farming based on the Internet of Things

Abstract

The invention discloses a fishery farming intelligent monitoring system based on the Internet of Things, belongs to the technical field of fishery farming monitoring, and comprises a platform end and a user end; the platform end comprises a collection and analysis module, an information module, and a technology reserve module; the collection and analysis module is used for performing collection demand analysis, determining various monitoring recommendation demands, and setting various collection devices according to various monitoring recommendation demands; the technology reserve module is used for setting various farming monitoring modes; the user end comprises a product communication module, a monitoring module, a monitoring and analysis module, a display module, and a farming adjustment module; the product communication module is used for determining a monitoring application mode and a monitoring management mode; the monitoring module is used for performing real-time monitoring of aquaculture and obtaining monitoring data; the monitoring and analysis module is used for analyzing the monitoring data and obtaining monitoring and analysis results; the display module is used for processing the monitoring data and the monitoring and analysis results to form display data; and the farming adjustment module is used for performing farming adjustment management.

Description

Technical Field

[0001] The present invention belongs to the technical field of fishery breeding monitoring, and in particular is a fishery breeding intelligent monitoring system based on the Internet of Things. Background Art

[0002] With the gradual reduction of global fishery resources and the increasing attention of consumers to food safety, traditional fishery farming methods have been unable to meet market demand. In order to improve farming efficiency and ensure the quality and safety of aquatic products, the concept of smart fishery has emerged. Smart fishery uses modern information technology and Internet of Things technology to intelligently manage and optimize various links such as fishery production, management, and sales. By deploying various sensors, water quality parameters such as temperature, dissolved oxygen, pH value, etc. can be monitored in real time, providing important data support for farming companies. However, these systems still have some shortcomings. Traditional farming monitoring systems can often only monitor specific farming species and lack flexibility and versatility. This leads to the need for farming companies to frequently replace or adjust the monitoring system when facing changes in market demand, which not only increases costs but also affects farming efficiency. Moreover, it is often only possible to perform simple data viewing and alarm reception, and it is impossible to dynamically change the monitored aquatic species according to user needs. This limits the ability of users to flexibly adjust farming strategies according to market demand. Often only fixed monitoring standards and farming strategies can be provided, and it is impossible to dynamically match the corresponding monitoring standards and farming strategies according to the aquatic species changed by users; resulting in poor flexibility.

[0003] Based on this, in order to solve the above problems, the present invention provides a fishery farming intelligent monitoring system based on the Internet of Things. Summary of the invention

[0004] In order to solve the problems existing in the above-mentioned solutions, the present invention provides a fishery farming intelligent monitoring system based on the Internet of Things.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A fishery farming intelligent monitoring system based on the Internet of Things, including a platform end and a user end;

[0007] The platform end includes a collection and analysis module, an information module, and a technology reserve module;

[0008] The collection and analysis module is used to perform collection demand analysis, determine various monitoring recommendation requirements, and set various collection devices according to the monitoring recommendation requirements.

[0009] Furthermore, the method for collecting demand analysis is:

[0010] Collecting characteristic data of each aquaculture combination and the combination corresponding to each aquaculture combination; conducting monitoring demand analysis on each aquaculture combination, and determining the monitoring item combination corresponding to each aquaculture combination;

[0011] Identify each aquaculture combination with the same monitoring item combination, and integrate the combination characteristic data corresponding to each aquaculture combination to form the combination characteristic data corresponding to the monitoring item combination;

[0012] Evaluate each combination of monitoring items to determine the recommended requirements for each monitoring.

[0013] Furthermore, the method for evaluating each combination of monitoring items is as follows:

[0014] Step SA1: Obtain the number of product types and product range required by the platform; identify the combination feature data of each monitoring item combination, screen each monitoring item combination according to the product range and each combination feature data, and eliminate each monitoring item combination outside the product range; mark the remaining monitoring item combinations as preliminary screening combinations;

[0015] Step SA2: Mark the number of product types as M, where M is a positive integer, and select M preliminary screening combinations from each of the preliminary screening combinations and mark them as reference combinations;

[0016] Step SA3: Calculate the combination difference value between each of the preliminary screening combinations and each of the benchmark combinations; classify each of the preliminary screening combinations and the benchmark combination with the smallest combination difference value into one category to obtain each merged classification;

[0017] Step SA4: adjusting the benchmark combination in each of the combined classifications;

[0018] Step SA5: When the sum of the difference values ​​between the primary screening combinations and the combined classification benchmark combination cannot be reduced any further, proceed to step SA6; otherwise, return to step SA3;

[0019] Step SA6: Identify each preliminary screening combination corresponding to the merged classification; calculate the combination priority value of each preliminary screening combination, determine each target combination according to each combination priority value, and set monitoring recommendation requirements according to each target combination.

[0020] Furthermore, the method of adjusting the benchmark combination in each merged classification in step SA4 includes:

[0021] Re-marking the benchmark combination in the combined classification as a preliminary screening combination, and calculating the eccentricity value of each preliminary screening combination in the combined classification;

[0022] The calculation formula of eccentricity is: ;

[0023] Where: PX is the deviation value; ZCi represents the combined difference value between the corresponding initial screening combination and the corresponding initial screening combination in the combined classification, i=1, 2, ..., n, n is a positive integer;

[0024] Select the initial screening combination with the smallest eccentricity value as the benchmark combination.

[0025] The information module is used to generate corresponding collection device information according to each collection device, and display each collection device information.

[0026] The technology reserve module is used to set various aquaculture monitoring methods and establish a corresponding technology reserve library based on each aquaculture monitoring method; the technology reserve library is used to store each aquaculture monitoring method and the reserve monitoring method and aquaculture combination corresponding to each aquaculture monitoring method.

[0027] Furthermore, the setting method of the breeding monitoring method includes:

[0028] Acquire all aquaculture combinations and the corresponding monitoring item combinations of each aquaculture combination in real time; acquire the information of each collection device, determine the monitoring method of each aquaculture combination according to the monitoring item combination and the collection device information, and mark it as the reserve monitoring method; set the corresponding aquaculture monitoring method for each reserve monitoring method.

[0029] The user end includes a product communication module, a monitoring module, a monitoring and analysis module, a display module and a breeding adjustment module;

[0030] The product communication module is used for users to communicate with the platform about products and determine monitoring application methods and monitoring management methods.

[0031] Furthermore, the methods for determining the monitoring application mode and the monitoring management mode include:

[0032] Acquire information of each collection device in real time; identify the user's aquaculture information, and match each reserve monitoring method and aquaculture monitoring method from the technical reserve library according to the aquaculture information;

[0033] The reserve monitoring methods and breeding monitoring methods are displayed to the user, and the user determines the monitoring application method and the monitoring management method based on the displayed reserve monitoring methods and breeding monitoring methods.

[0034] The monitoring module is used to monitor aquaculture in real time, obtain a monitoring application method, arrange various collection devices based on the monitoring application method, perform real-time collection through each of the collection devices, obtain corresponding monitoring data; and send the monitoring data to the monitoring analysis module.

[0035] The monitoring and analysis module is used to analyze the monitoring data, obtain the monitoring management method, analyze the received monitoring data according to the monitoring management method, and obtain the corresponding monitoring and analysis results.

[0036] The display module is used to process the monitoring data and the monitoring analysis results, obtain the monitoring data and the monitoring analysis results in real time, obtain the user's display requirements, analyze the monitoring data and the monitoring analysis results according to the display requirements through a preset display model, form corresponding display data, and display the display data to the user in real time.

[0037] The aquaculture adjustment module is used to perform aquaculture adjustment management and set an aquaculture information map;

[0038] When the user makes an aquaculture adjustment, an aquaculture adjustment diagram is generated through the aquaculture information diagram; and aquaculture adjustment data is obtained according to the aquaculture adjustment diagram;

[0039] Evaluate whether the monitoring application mode meets the aquaculture monitoring needs according to the aquaculture adjustment data, and obtain a monitoring needs evaluation result, wherein the monitoring needs evaluation result includes not meeting the monitoring needs and meeting the monitoring needs;

[0040] When the monitoring demand assessment result shows that the monitoring demand is not met, make corresponding monitoring adjustments;

[0041] When the monitoring demand assessment result is that the monitoring demand is met, the corresponding breeding monitoring method is matched, the current monitoring management method is identified, and the monitoring management method is replaced by the breeding monitoring method.

[0042] Furthermore, the method for evaluating whether the monitoring application method meets the aquaculture monitoring needs based on the aquaculture adjustment data is as follows:

[0043] An evaluation method is set, and a monitoring evaluation model is established according to the evaluation method. The expression of the monitoring evaluation model is:

[0044] ;

[0045] Where: s is the aquaculture adjustment data, c is the aquaculture adjustment map, and v is the monitoring simulation data; the output data is the monitoring evaluation value KP (s, c, v);

[0046] Analyze through monitoring and evaluation model to obtain corresponding monitoring and evaluation value;

[0047] When the monitoring evaluation value is 1 or 2, the monitoring demand evaluation result is that the monitoring demand is not met;

[0048] When the monitoring evaluation value is 3, the monitoring demand evaluation result is that the monitoring demand is met.

[0049] Furthermore, the evaluation method is:

[0050] Determine the corresponding aquaculture combination according to the aquaculture adjustment data and the aquaculture adjustment map, match the corresponding reserve monitoring method and aquaculture monitoring method according to the aquaculture combination, perform a preliminary monitoring assessment according to the obtained reserve monitoring method and aquaculture monitoring method, and obtain a preliminary monitoring result, wherein the preliminary monitoring result includes whether the preliminary monitoring requirements are met or not met;

[0051] When the initial evaluation result does not meet the initial monitoring result, the evaluation is terminated;

[0052] When the initial assessment result meets the preliminary monitoring result, monitoring simulation data is obtained, and a second-order monitoring assessment is performed based on the monitoring simulation data and the aquaculture adjustment map to obtain second-order monitoring results. The second-order monitoring results include meeting the second-order monitoring requirements and not meeting the second-order monitoring requirements.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] By setting up a variety of IoT-based monitoring sensors on the platform, it can meet the monitoring needs of various aquaculture in the same water area; it solves the limitation that traditional monitoring systems can only monitor specific aquaculture species, allowing users to choose corresponding sensors for deployment according to actual needs, greatly improving the flexibility and versatility of the system.

[0055] Secondly, the system allows users to dynamically change the types of aquatic products to be monitored through the user terminal. This function enables users to adjust the monitoring objects in a timely manner according to changes in market demand without having to replace or adjust the monitoring system. This not only reduces the user's cost, but also improves the breeding efficiency and market response speed.

[0056] Furthermore, the platform can dynamically match the corresponding monitoring standards and breeding strategies according to the aquatic species changed by the user. This intelligent matching mechanism ensures that the monitoring system can be adaptively adjusted according to the needs of different breeding species, thereby improving the accuracy and practicality of monitoring. At the same time, this also provides users with a more convenient and efficient breeding management experience.

[0057] In addition, the system is highly flexible and scalable. After one deployment, users can implement subsequent monitoring and adjustment of multiple aquatic products without complicated system transformation or upgrade. This feature enables the system to adapt to different scales of breeding enterprises and different types of aquatic products, and has a wide range of application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0059] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0060] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] like Figure 1 As shown, a fishery farming intelligent monitoring system based on the Internet of Things includes a platform end and a user end;

[0062] The platform end is established and used by the platform party, including a collection and analysis module, an information module, and a technology reserve module;

[0063] The collection and analysis module is used to perform collection demand analysis, determine various monitoring recommendation requirements, and then assist the platform to set up various types of collection equipment for subsequent user selection.

[0064] In one embodiment, the method for performing collection demand analysis is:

[0065] Based on the existing big data technology, various aquaculture combinations of current fishery farmers and the combined characteristic data such as breeding scale and number of farmers corresponding to each aquaculture combination are determined. Aquaculture combination is a combination of multiple aquatic species co-breeding; because many aquaculture farmers will carry out multiple aquaculture to increase economic benefits, they will have multiple aquaculture combinations; the monitoring needs of each aquaculture combination are analyzed to determine which data needs to be collected in order to realize the monitoring of the aquaculture combination, such as temperature, dissolved oxygen, pH value, microbial species, content, aquatic density, etc., marked as monitoring items, one monitoring item corresponds to one monitoring data, such as the monitoring item corresponding to temperature; identify each aquaculture combination with the same monitoring item combination, integrate the corresponding combination characteristic data of each aquaculture combination, form the combination characteristic data corresponding to the monitoring item combination, and realize the deduplication of the monitoring item combination, that is, the situation where one monitoring item combination corresponds to multiple aquaculture combinations is deduplicated, and the corresponding combination characteristic data are integrated;

[0066] Identify the combined characteristic data corresponding to each monitoring item combination, evaluate each monitoring item combination, and determine the recommended requirements for each monitoring; the platform will then design and build corresponding collection equipment based on the recommended requirements for each detection.

[0067] In one embodiment, the method for evaluating each combination of monitoring items is: performing screening evaluation based on existing technologies and determining through manual evaluation by staff.

[0068] In one embodiment, the method for evaluating each monitoring item combination is:

[0069] Step SA1: Obtain the number of product types required by the platform, that is, the number of types of collection equipment required, which refers to equipment that collects different data combinations, such as temperature and pH value as one type, and temperature, dissolved oxygen, and pH value as a new type. The platform sets the product range, which refers to the range of farmers and breeding needs for which the platform develops products. The initial state is generally the range corresponding to the combined characteristic data corresponding to all monitoring item combinations. The corresponding product range will be adjusted later according to the platform's business needs;

[0070] Identify the combination characteristic data corresponding to each monitoring item combination, screen each monitoring item combination according to the product range and each combination characteristic data, and eliminate each monitoring item combination outside the product range;

[0071] Mark the remaining monitoring item combinations as initial screening combinations;

[0072] Step SA2: mark the number of product types as M, where M is a positive integer, and select M preliminary screening combinations from each preliminary screening combination as the benchmark combination;

[0073] Step SA3: Calculate the combination difference value between each preliminary screening combination and each benchmark combination; classify each preliminary screening combination and the benchmark combination with the smallest combination difference value into one category to obtain each combined classification;

[0074] Step SA4: Adjust the benchmark combination in each merged classification;

[0075] Step SA5: When the sum of the difference values ​​between each initial screening combination and the corresponding combined classification benchmark combination cannot be reduced any further, proceed to step SA6; otherwise, return to step SA3;

[0076] Step SA6: Identify the initial screening combinations corresponding to the merged classification, including the corresponding benchmark combinations; calculate the combination priority value of each initial screening combination, determine each target combination according to the priority value of each combination, that is, the initial screening combination with the highest priority, and set monitoring recommendation requirements according to each target combination.

[0077] In one embodiment, the calculation method of the combined difference value is: directly calculate based on the difference ratio of the monitoring items of the combination of two monitoring items, such as the combination of two monitoring items A: temperature, dissolved oxygen, pH value and B: temperature, pH value, then the combined difference value of A→B is 1 / 3, and the combined difference value of B→A is 1 / 2.

[0078] In one embodiment, the combined difference value is calculated by setting a weight coefficient for each monitoring item based on the previous embodiment, and then multiplying the weight coefficient by the corresponding weight coefficient, such as 1 / 2×weight coefficient.

[0079] In one embodiment, the combined difference values ​​between the monitoring item combinations may also be calculated based on the existing difference calculation method.

[0080] Methods for adjusting the benchmark portfolio in each consolidation category include:

[0081] Re-label the benchmark combination in the combined classification as the initial screening combination, and calculate the eccentricity value of each initial screening combination in the combined classification;

[0082] The calculation formula of eccentricity is: ; Where: PX is the deviation value; ZCi represents the difference between the initial screening combination and other initial screening combinations in the combined classification, i=1, 2, ..., n, n is a positive integer;

[0083] Select the initial screening combination with the smallest eccentricity value as the benchmark combination.

[0084] In one embodiment, the combination priority value of each initial screening combination is determined based on the estimated future economic benefits of the existing technology; for example, it is estimated based on the number of farmers, scale, and estimated costs.

[0085] In one embodiment, the combination priority value may also be evaluated in combination with various existing priority value evaluation methods to determine the priority of each initial combination.

[0086] The information module is used to generate corresponding collection device information according to each collection device, and display each collection device information.

[0087] The collection equipment information includes various monitoring items, prices, applicable aquatic species, pictures and other related information, which are used to display to users to facilitate users to choose appropriate monitoring methods.

[0088] The technical reserve module is used to set various breeding monitoring methods, and the breeding monitoring methods are used to monitor aquaculture based on corresponding monitoring data, and obtain in real time various aquaculture combinations and monitoring item combinations corresponding to each aquaculture combination; determine the monitoring method of each aquaculture combination according to each monitoring item combination and each collection device information, and mark it as a reserve monitoring method; set a corresponding breeding monitoring method for each reserve monitoring method.

[0089] Integrate and store various reserve monitoring methods, breeding monitoring methods, and aquaculture combinations into a preset technical reserve library.

[0090] In one embodiment, once the specific reserve monitoring method is clarified, the corresponding aquaculture monitoring method can be set up based on various existing aquaculture monitoring needs; such as parameter warning, parameter prediction warning, intelligent regulation, etc.

[0091] The user terminal is used by users and includes a product communication module, a monitoring module, a monitoring and analysis module, a display module and a breeding adjustment module;

[0092] The product communication module is used for users to communicate with the platform about products and obtain the information of each collection device displayed by the information module in real time;

[0093] Obtain the user's aquaculture information, including aquaculture types, breeding area information, breeding quantity and other related information; the user inputs and uploads it; according to the user's aquaculture information, match the various reserve monitoring methods and breeding monitoring methods that meet the requirements from the platform's technical reserve library; meeting the requirements means meeting the breeding monitoring needs.

[0094] Various reserve monitoring methods and breeding monitoring methods are displayed to users, and users determine the applied reserve monitoring method and breeding monitoring method through consultation with platform staff, and mark the applied reserve monitoring method and breeding monitoring method as monitoring application method and monitoring management method respectively.

[0095] The monitoring module is used to monitor the aquatic products raised by the user and obtain the corresponding monitoring data in real time; and send the monitoring data to the monitoring analysis module; specifically, various collection devices are set based on the monitoring application method to achieve subsequent monitoring.

[0096] The monitoring and analysis module is used to analyze the monitoring data, obtain the monitoring management method, analyze the received monitoring data according to the monitoring management method, and obtain the corresponding monitoring and analysis results.

[0097] The display module is used to process the monitoring data and monitoring analysis results, and obtain the monitoring data and monitoring analysis results in real time. The platform establishes a display model, and the display model is used to analyze the monitoring data and monitoring analysis results according to corresponding display requirements, form corresponding display data, and display the display data to users in real time.

[0098] The display requirements are set by the user, such as curves, tables, bar charts, highlight marks and other display forms, which are set according to user needs.

[0099] In one embodiment, the platform may also preset several display modes for users to choose from, so as to facilitate fixing the corresponding display mode.

[0100] The display model is established based on existing technologies and is used to realize the intelligent generation of display data. For example, it is established based on neural networks such as CNN networks and DNN networks. Subsequently, the platform sets up corresponding training sets for training.

[0101] The aquaculture adjustment module is used to make corresponding monitoring adjustments when changes occur in the user's aquaculture; obtain the user's original aquaculture information, generate an aquaculture information map, and display the aquaculture water area information in a plane or three-dimensional form, so as to facilitate the intuitive display of each segmented aquaculture area, and mark the corresponding aquaculture information in the corresponding area;

[0102] When the user makes an aquaculture adjustment, the user adjusts the aquaculture information chart and marks the adjusted aquaculture information chart as an aquaculture adjustment chart; the aquaculture adjustment part is determined according to the aquaculture adjustment chart, such as changing the aquaculture type, aquaculture scale, etc., and marked as aquaculture adjustment data;

[0103] Analyze the current monitoring application mode based on the aquaculture adjustment data to see whether it can meet the subsequent aquaculture monitoring needs, that is, whether the current monitoring items can achieve the subsequent monitoring of various aquatic species, and obtain the corresponding monitoring needs assessment results, including whether the monitoring needs are met or not;

[0104] When the monitoring demand assessment result shows that the monitoring demand is not met, corresponding monitoring adjustments are made; and re-evaluation is performed later until the monitoring demand is met;

[0105] When the monitoring needs assessment result meets the monitoring needs, the corresponding breeding monitoring method is matched, and the matching breeding monitoring method replaces the original monitoring management method; normal monitoring can be carried out subsequently, the corresponding monitoring data can be obtained, and the data is processed based on the replaced monitoring management method, and then displayed according to the display module.

[0106] In one embodiment, the determination of the need for aquaculture monitoring according to the aquaculture adjustment data may be made based on existing technologies.

[0107] In one embodiment, the method for evaluating whether the monitoring application mode meets the aquaculture monitoring requirements according to the aquaculture adjustment data is as follows:

[0108] Set the evaluation method;

[0109] A monitoring and evaluation model is established according to the evaluation method. The expression of the monitoring and evaluation model is: ;

[0110] Where: s is the aquaculture adjustment data, c is the aquaculture adjustment map, v is the monitoring simulation data, the monitoring simulation data is the simulated collection data set according to the current collection equipment, which is used to understand its collection situation in each water area, and the output data is the monitoring evaluation value KP (s, c, v);

[0111] Analyze through monitoring and evaluation model to obtain corresponding monitoring and evaluation value;

[0112] When the monitoring evaluation value is 1 or 2, the monitoring demand evaluation result is that the monitoring demand is not met; monitoring adjustments can be made based on the specific monitoring evaluation value, such as adding appropriate collection equipment, adjusting the location of the collection equipment, etc.;

[0113] When the monitoring evaluation value is 3, the monitoring demand evaluation result is that the monitoring demand is met.

[0114] The evaluation method is:

[0115] Determine the corresponding aquaculture combination according to the aquaculture adjustment data and the aquaculture adjustment map, match the corresponding reserve monitoring method and aquaculture monitoring method from the technical reserve library according to the aquaculture combination, and conduct a primary monitoring assessment based on the obtained reserve monitoring method and aquaculture monitoring method, that is, assess whether the initial monitoring needs are met, that is, the needs assessment before the simulation collection is not conducted. If it is directly determined that it cannot be achieved, there is no need to conduct subsequent simulation monitoring, and use the simulation monitoring data for analysis to reduce the amount of data analysis, such as comparing the currently applied monitoring application method and monitoring management method with the obtained reserve monitoring method and aquaculture monitoring method to determine whether the monitoring of the aquaculture combination is met; if the initial requirements are met, it is deemed to meet the primary monitoring requirements, and then a monitoring simulation is performed, that is, simulated monitoring is performed according to the positions of the existing collection equipment to obtain monitoring simulation data, and a second-order monitoring assessment is performed based on the monitoring simulation data and the aquaculture adjustment map to assess whether the existing monitoring data meets the monitoring needs of each aquatic product in the aquatic adjustment map. If this requirement is met, it is deemed to meet the second-order monitoring requirements; and then the final monitoring needs assessment result is obtained.

[0116] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0117] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A fishery farming intelligent monitoring system based on the Internet of Things, characterized in that: Including platform side and user side; The platform end includes a collection and analysis module, an information module and a technical reserve module; The acquisition analysis module is used to perform acquisition demand analysis, determine monitoring recommendation requirements, and set acquisition equipment according to the monitoring recommendation requirements; The information module is used to generate corresponding collection device information according to the collection device and display the collection device information; The technical reserve module is used to set the aquaculture monitoring method and establish a corresponding technical reserve library based on the aquaculture monitoring method; the technical reserve library is used to store the aquaculture monitoring method and the reserve monitoring method and aquaculture combination corresponding to the corresponding aquaculture monitoring method; The user end includes a product communication module, a monitoring module, a monitoring and analysis module, a display module and a breeding adjustment module; The product communication module is used for users to communicate with the platform about products and determine the monitoring application method and monitoring management method; The monitoring module is used to monitor aquaculture in real time, obtain a monitoring application mode, arrange collection equipment based on the monitoring application mode, collect data in real time through the collection equipment, obtain corresponding monitoring data; and send the monitoring data to the monitoring analysis module; The monitoring and analysis module is used to analyze the monitoring data, obtain the monitoring management method, analyze the received monitoring data according to the monitoring management method, and obtain the corresponding monitoring and analysis results; The display module is used to process the monitoring data and the monitoring analysis results, obtain the monitoring data and the monitoring analysis results in real time, obtain the user's display requirements, analyze the monitoring data and the monitoring analysis results according to the display requirements through a preset display model, form corresponding display data, and display the display data to the user in real time; The aquaculture adjustment module is used to perform aquaculture adjustment management and set an aquaculture information map; When the user makes an aquaculture adjustment, an aquaculture adjustment diagram is generated through the aquaculture information diagram; and aquaculture adjustment data is obtained according to the aquaculture adjustment diagram; Evaluate whether the monitoring application mode meets the aquaculture monitoring needs according to the aquaculture adjustment data, and obtain a monitoring needs evaluation result, wherein the monitoring needs evaluation result includes not meeting the monitoring needs and meeting the monitoring needs; When the monitoring needs assessment result shows that the monitoring needs are not met, corresponding monitoring adjustments are made; When the monitoring demand assessment result is that the monitoring demand is met, the corresponding breeding monitoring method is matched, the current monitoring management method is identified, and the monitoring management method is replaced by the breeding monitoring method; The method for collecting demand analysis is: Collecting aquaculture combinations and combination characteristic data corresponding to the corresponding aquaculture combinations; conducting monitoring demand analysis on the aquaculture combinations, and determining a combination of monitoring items corresponding to the aquaculture combinations; Identify aquaculture combinations with the same monitoring item combination, and integrate the combination characteristic data corresponding to the aquaculture combinations to form the combination characteristic data corresponding to the monitoring item combination; Evaluate the combination of monitoring items and determine the monitoring recommendation requirements.

2. According to the Internet of Things-based fishery farming intelligent monitoring system of claim 1, it is characterized in that: The method for evaluating the combination of monitoring items is: Step SA1: Obtain the number of product types and product range required by the platform; identify the combination characteristic data of the monitoring item combination, screen the monitoring item combination according to the product range and the combination characteristic data, and eliminate the monitoring item combination outside the product range; mark the remaining monitoring item combination as the initial screening combination; Step SA2: Mark the number of product types as M, where M is a positive integer, and select M preliminary screening combinations from the preliminary screening combinations as reference combinations; Step SA3: Calculate the combination difference value between the initial screening combination and the reference combination; classify the reference combination with the smallest combination difference value between the initial screening combination and the reference combination into one category to obtain a combined classification; Step SA4: adjusting the benchmark combination in the merged classification; Step SA5: When the sum of the difference values ​​between the initial screening combination and the combined classification benchmark combination cannot be reduced any further, proceed to step SA6; otherwise, return to step SA3; Step SA6: Identify the initial screening combination corresponding to the combined classification; calculate the combination priority value of the initial screening combination, determine the target combination according to the combination priority value, and set the monitoring recommendation requirements according to the target combination.

3. The fishery farming intelligent monitoring system based on the Internet of Things according to claim 2 is characterized in that: The method of adjusting the benchmark combination in the combined classification in step SA4 includes: Re-marking the benchmark combination in the combined classification as a preliminary screening combination, and calculating the eccentricity value of the preliminary screening combination in the combined classification; The calculation formula of eccentricity is: ; Where: PX is the deviation value; ZCi represents the combined difference value between the corresponding initial screening combination and the corresponding initial screening combination in the combined classification, i=1, 2, ..., n, n is a positive integer; Select the initial screening combination with the smallest eccentricity value as the benchmark combination.

4. The fishery farming intelligent monitoring system based on the Internet of Things according to claim 1 is characterized in that: The methods for setting up the aquaculture monitoring method include: Acquire the existing aquaculture combinations and the monitoring item combinations corresponding to the corresponding aquaculture combinations in real time; acquire the collection equipment information, determine the monitoring method of the corresponding aquaculture combination according to the monitoring item combination and the collection equipment information, and mark it as the reserve monitoring method; set the corresponding aquaculture monitoring method for the reserve monitoring method.

5. The fishery farming intelligent monitoring system based on the Internet of Things according to claim 1 is characterized in that: Methods for determining monitoring application methods and monitoring management methods include: Acquire collection equipment information in real time; identify the user's aquaculture information, and match the reserve monitoring method and the aquaculture monitoring method from the technology reserve library according to the aquaculture information; The reserve monitoring method and the breeding monitoring method are displayed to the user, and the user determines the monitoring application method and the monitoring management method based on the displayed reserve monitoring method and the breeding monitoring method.

6. The fishery farming intelligent monitoring system based on the Internet of Things according to claim 5 is characterized in that: The method for evaluating whether the monitoring application method meets the aquaculture monitoring needs based on the aquaculture adjustment data is: An evaluation method is set, and a monitoring evaluation model is established according to the evaluation method. The expression of the monitoring evaluation model is: ； Where: s is the aquaculture adjustment data, c is the aquaculture adjustment map, and v is the monitoring simulation data; the output data is the monitoring evaluation value KP (s, c, v); Analyze through monitoring and evaluation model to obtain corresponding monitoring and evaluation value; When the monitoring evaluation value is 1 or 2, the monitoring demand evaluation result is that the monitoring demand is not met; When the monitoring evaluation value is 3, the monitoring demand evaluation result is that the monitoring demand is met.

7. The fishery farming intelligent monitoring system based on the Internet of Things according to claim 6 is characterized in that: The evaluation method is: Determine the corresponding aquaculture combination according to the aquaculture adjustment data and the aquaculture adjustment map, match the corresponding reserve monitoring method and aquaculture monitoring method according to the aquaculture combination, perform a preliminary monitoring assessment according to the obtained reserve monitoring method and aquaculture monitoring method, and obtain a preliminary monitoring result, wherein the preliminary monitoring result includes whether the preliminary monitoring requirements are met or not met; When the initial evaluation result does not meet the initial monitoring result, the evaluation is terminated; When the initial assessment result meets the preliminary monitoring result, monitoring simulation data is obtained, and a second-order monitoring assessment is performed based on the monitoring simulation data and the aquaculture adjustment map to obtain second-order monitoring results. The second-order monitoring results include meeting the second-order monitoring requirements and not meeting the second-order monitoring requirements.

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